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检索条件"机构=Pattern Recognition and Human Language"
401 条 记 录,以下是21-30 订阅
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Towards a Better Evaluation of Metrics for Machine Translation  5
Towards a Better Evaluation of Metrics for Machine Translati...
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5th Conference on Machine Translation, WMT 2020
作者: Stanchev, Peter Wang, Weiyue Ney, Hermann Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen52056 Germany
An important aspect of machine translation is its evaluation, which can be achieved through the use of a variety of metrics. To compare these metrics, the workshop on statistical machine translation annually evaluates... 详细信息
来源: 评论
Improving language Model Integration for Neural Machine Translation
arXiv
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arXiv 2023年
作者: Herold, Christian Gao, Yingbo Zeineldeen, Mohammad Ney, Hermann Human Language Technology and Pattern Recognition Group Computer Science Department RWTH Aachen University AachenD-52056 Germany
The integration of language models for neural machine translation has been extensively studied in the past. It has been shown that an external language model, trained on additional target-side monolingual data, can he... 详细信息
来源: 评论
On Search Strategies for Document-Level Neural Machine Translation
arXiv
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arXiv 2023年
作者: Herold, Christian Ney, Hermann Human Language Technology and Pattern Recognition Group Computer Science Department RWTH Aachen University AachenD-52056 Germany
Compared to sentence-level systems, document-level neural machine translation (NMT) models produce a more consistent output across a document and are able to better resolve ambiguities within the input. There are many... 详细信息
来源: 评论
Document-Level language Models for Machine Translation
arXiv
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arXiv 2023年
作者: Petrick, Frithjof Herold, Christian Petrushkov, Pavel Khadivi, Shahram Ney, Hermann eBay Inc. Aachen Germany Human Language Technology and Pattern Recognition Group RWTH Aachen University Aachen Germany
Despite the known limitations, most machine translation systems today still operate on the sentence-level. One reason for this is, that most parallel training data is only sentence-level aligned, without document-leve... 详细信息
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Improving Long Context Document-Level Machine Translation
arXiv
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arXiv 2023年
作者: Herold, Christian Ney, Hermann Human Language Technology and Pattern Recognition Group Computer Science Department RWTH Aachen University AachenD-52056 Germany
Document-level context for neural machine translation (NMT) is crucial to improve the translation consistency and cohesion, the translation of ambiguous inputs, as well as several other linguistic phenomena. Many work... 详细信息
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Robust Knowledge Distillation from RNN-T Models with Noisy Training Labels Using Full-Sum Loss
Robust Knowledge Distillation from RNN-T Models with Noisy T...
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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
作者: Mohammad Zeineldeen Kartik Audhkhasi Murali Karthick Baskar Bhuvana Ramabhadran Computer Science Department Human Language Technology and Pattern Recognition RWTH Aachen University Aachen Germany Google LLC New York
This work studies knowledge distillation (KD) and addresses its constraints for recurrent neural network transducer (RNN-T) models. In hard distillation, a teacher model transcribes large amounts of unlabelled speech ... 详细信息
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Enhancing and Adversarial: Improve ASR with Speaker Labels
Enhancing and Adversarial: Improve ASR with Speaker Labels
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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
作者: Wei Zhou Haotian Wu Jingjing Xu Mohammad Zeineldeen Christoph Lüscher Ralf Schlüter Hermann Ney Computer Science Department Human Language Technology and Pattern Recognition RWTH Aachen University Aachen Germany AppTek GmbH Aachen Germany
ASR can be improved by multi-task learning (MTL) with domain enhancing or domain adversarial training, which are two opposite objectives with the aim to increase/decrease domain variance towards domain-aware/agnostic ... 详细信息
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Lattice-Free Sequence Discriminative Training for Phoneme-Based Neural Transducers
Lattice-Free Sequence Discriminative Training for Phoneme-Ba...
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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
作者: Zijian Yang Wei Zhou Ralf Schlüter Hermann Ney Computer Science Department Human Language Technology and Pattern Recognition RWTH Aachen University Aachen Germany AppTek GmbH Aachen Germany
Recently, RNN-Transducers have achieved remarkable results on various automatic speech recognition tasks. However, lattice-free sequence discriminative training methods, which obtain superior performance in hybrid mod... 详细信息
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AnnoTheia: A Semi-Automatic Annotation Toolkit for Audio-Visual Speech Technologies  30
AnnoTheia: A Semi-Automatic Annotation Toolkit for Audio-Vis...
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Joint 30th International Conference on Computational Linguistics and 14th International Conference on language Resources and Evaluation, LREC-COLING 2024
作者: Acosta-Triana, José M. Gimeno-Gómez, David Martínez-Hinarejos, Carlos D. ValgrAI - Valencian Graduate School and Research Network of Artificial Intelligence Camino de Vera s/n 3Q Building València46022 Spain Pattern Recognition and Human Language Technologies Research Center Universitat Politècnica de València Camino de Vera s/n València46022 Spain
More than 7,000 known languages are spoken around the world. However, due to the lack of annotated resources, only a small fraction of them are currently covered by speech technologies. Albeit self-supervised speech r... 详细信息
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Efficient Utilization of Large Pre-Trained Models for Low Resource ASR
Efficient Utilization of Large Pre-Trained Models for Low Re...
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Acoustics, Speech, and Signal Processing Workshops (ICASSPW), IEEE International Conference on
作者: Peter Vieting Christoph Lüscher Julian Dierkes Ralf Schlüter Hermann Ney Computer Science Department Human Language Technology and Pattern Recognition Group RWTH Aachen University Aachen Germany AppTek GmbH Aachen Germany
Unsupervised representation learning has recently helped automatic speech recognition (ASR) to tackle tasks with limited labeled data. Following this, hardware limitations and applications give rise to the question ho...
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